• 제목/요약/키워드: Quadratic Approximation Algorithm

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An efficient algorithm for the non-convex penalized multinomial logistic regression

  • Kwon, Sunghoon;Kim, Dongshin;Lee, Sangin
    • Communications for Statistical Applications and Methods
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    • 제27권1호
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    • pp.129-140
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    • 2020
  • In this paper, we introduce an efficient algorithm for the non-convex penalized multinomial logistic regression that can be uniformly applied to a class of non-convex penalties. The class includes most non-convex penalties such as the smoothly clipped absolute deviation, minimax concave and bridge penalties. The algorithm is developed based on the concave-convex procedure and modified local quadratic approximation algorithm. However, usual quadratic approximation may slow down computational speed since the dimension of the Hessian matrix depends on the number of categories of the output variable. For this issue, we use a uniform bound of the Hessian matrix in the quadratic approximation. The algorithm is available from the R package ncpen developed by the authors. Numerical studies via simulations and real data sets are provided for illustration.

이점 대각 이차 근사화 기법을 쌍대기법에 적용한 순차적 근사 최적설계 (Sequential Approximate Optimization by Dual Method Based on Two-Point Diagonal Quadratic Approximation)

  • 박선호;정상진;정승현;최동훈
    • 대한기계학회논문집A
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    • 제35권3호
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    • pp.259-266
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    • 2011
  • 본 논문에서는 SD-TDQAO (Sequential Dual - Two-point Diagonal Quadratic Approximate Optimization)라는 쌍대기법을 이용한 순차적 최적설계 알고리즘을 제안한다. 이 방법은 비선형 목적함수와 제한조건이 포함되어 있는 공학적인 문제를 효과적으로 풀 수 있도록 하는데 목적이 있다. 기존의 볼록성과 분리성이 만족되지 않는 eTDQA2 방법을 이용하여 쌍대기법에 이용할 수 있도록 이차 근사함수의 헤시언 대각요소에 이를 적용하여 쉽게 볼록성과 분리성을 보장할 수 있도록 하였다. 또한 이를 수학적 예제와 위상 최적설계문제를 통해 기존의 쌍대기법 알고리즘인 MMA 와의 비교로 그 성능을 입증하였다.

함수근사를 위한 서포트 벡터 기계의 커널 애더트론 알고리즘 (Kernel Adatron Algorithm of Support Vector Machine for Function Approximation)

  • 석경하;황창하
    • 한국정보처리학회논문지
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    • 제7권6호
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    • pp.1867-1873
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    • 2000
  • 함수근사는 과학과 고학부야에서 공범위하게 응용된다. 시포트 벡터 기계(support vector machine, SVM)는 원래 분류를 위해 계안되어져 문자인식, 얼굴인식 등의 응용분야에서 좋은 결과를 보여주고 있다. 최근 SVM이론 함수근사로 확장되어 많이 활용되려 하고 있다. 그러나 함수근사를 위한 SVM 알고리즘은 QP(quadratic proramming)문제와 관련되어있어 계산에 시간이 걸리며 QP를 위한 패키지가 있어야 한다. 본 논문에서는 함수근사를 위해 커널-애더트론 알고리즘을 이용한 SVM을 제안하고 QP를 이용한 SVM과 성능을 비교하고자 한다.

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A SUCCESSIVE QUADRATIC PROGRAMMING ALGORITHM FOR SDP RELAXATION OF THE BINARY QUADRATIC PROGRAMMING

  • MU XUEWEN;LID SANYANG;ZHANG YALING
    • 대한수학회보
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    • 제42권4호
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    • pp.837-849
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    • 2005
  • In this paper, we obtain a successive quadratic programming algorithm for solving the semidefinite programming (SDP) relaxation of the binary quadratic programming. Combining with a randomized method of Goemans and Williamson, it provides an efficient approximation for the binary quadratic programming. Furthermore, its convergence result is given. At last, We report some numerical examples to compare our method with the interior-point method on Maxcut problem.

Multiclass Support Vector Machines with SCAD

  • Jung, Kang-Mo
    • Communications for Statistical Applications and Methods
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    • 제19권5호
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    • pp.655-662
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    • 2012
  • Classification is an important research field in pattern recognition with high-dimensional predictors. The support vector machine(SVM) is a penalized feature selector and classifier. It is based on the hinge loss function, the non-convex penalty function, and the smoothly clipped absolute deviation(SCAD) suggested by Fan and Li (2001). We developed the algorithm for the multiclass SVM with the SCAD penalty function using the local quadratic approximation. For multiclass problems we compared the performance of the SVM with the $L_1$, $L_2$ penalty functions and the developed method.

An EM Algorithm for a Doubly Smoothed MLE in Normal Mixture Models

  • Seo, Byung-Tae
    • Communications for Statistical Applications and Methods
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    • 제19권1호
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    • pp.135-145
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    • 2012
  • It is well known that the maximum likelihood estimator(MLE) in normal mixture models with unequal variances does not fall in the interior of the parameter space. Recently, a doubly smoothed maximum likelihood estimator(DS-MLE) (Seo and Lindsay, 2010) was proposed as a general alternative to the ordinary maximum likelihood estimator. Although this method gives a natural modification to the ordinary MLE, its computation is cumbersome due to intractable integrations. In this paper, we derive an EM algorithm for the DS-MLE under normal mixture models and propose a fast computational tool using a local quadratic approximation. The accuracy and speed of the proposed method is then presented via some numerical studies.

GMDH 알고리즘과 다항식 퍼지추론에 기초한 퍼지 다항식 뉴럴 네트워크 (Fuzzy Polynomial Neural Networks based on GMDH algorithm and Polynomial Fuzzy Inference)

  • 박호성;윤기찬;오성권
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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    • pp.130-133
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    • 2000
  • In this paper, a new design methodology named FNNN(Fuzzy Polynomial Neural Network) algorithm is proposed to identify the structure and parameters of fuzzy model using PNN(Polynomial Neural Network) structure and a fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and modified quadratic besides the biquadratic polynomial used in the GMDH. The premise of fuzzy inference rules defines by triangular and gaussian type membership function. The fuzzy inference method uses simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture Several numerical example are used to evaluate the performance of out proposed model. Also we used the training data and testing data set to obtain a balance between the approximation and generalization of proposed model.

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순차적 다항식 근사화를 적용한 효율적 선탐색기법의 개발 (Development of an Efficient Line Search Method by Using the Sequential Polynomial Approximation)

  • 김민수;최동훈
    • 대한기계학회논문집
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    • 제19권2호
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    • pp.433-442
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    • 1995
  • For the line search of a multi-variable optimization, an efficient algorithm is presented. The algorithm sequentially employs several polynomial approximations such as 2-point quadratic interpolation, 3-point cubic interpolation/extrapolation and 4-point cubic interpolation/extrapolation. The order of polynomial function is automatically increased for improving the accuracy of approximation. The method of approximation (interpolation or extrapolation) is automatically switched by checking the slope information of the sample points. Also, for selecting the initial step length along the descent vector, a new approach is presented. The performance of the proposed method is examined by solving typical test problems such as mathematical problems, mechanical design problems and dynamic response problems.

Optimum design of shape and size of truss structures via a new approximation method

  • Ahmadvand, Hosein;Habibi, Alireza
    • Structural Engineering and Mechanics
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    • 제76권6호
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    • pp.799-821
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    • 2020
  • The optimum design of truss structures is one of the significant categories in structural optimization that has widely been applied by researchers. In the present study, new mathematical programming called Consistent Approximation (CONAP) method is utilized for the simultaneous optimization of the size and shape of truss structures. The CONAP algorithm has already been introduced to optimize some structures and functions. In the CONAP algorithm, some important parameters are designed by employing design sensitivities to enhance the capability of the method and its consistency in various optimum design problems, especially structural optimization. The cross-sectional area of the bar elements and the nodal coordinates of the truss are assumed to be the size and shape design variables, respectively. The displacement, allowable stress and the Euler buckling stress are taken as the design constraints for the problem. In the proposed method, the primary optimization problem is replaced with a sequence of explicit sub-problems. Each sub-problem is efficiently solved using the sequential quadratic programming (SQP) algorithm. Several truss structures are designed by employing the CONAP method to illustrate the efficiency of the algorithm for simultaneous shape and size optimization. The optimal solutions are compared with some of the mathematical programming algorithms, the approximation methods and metaheuristic algorithms those reported in the literature. Results demonstrate that the accuracy of the optimization is improved and the convergence rate speeds up.

벨로우즈의 장착에 따른 자동차 배기계의 동특성 개선 및 벨로우즈의 최적위치 평가 (Improvement of the Vibrational Characteristics According to Attachment of Bellows and Evaluation of Bellows Optimal Position in Automobile Exhaust System)

  • 고병갑;이완익;박경진
    • 한국자동차공학회논문집
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    • 제2권3호
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    • pp.21-32
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    • 1994
  • The Problem of mechanical vibration is investigated for an automotive exhaust system. The vibrational reduction effect is systematically evaluated according to the attachment of the exhaust system. Moreover, the optimal attachment position of bellows is determined from the viewpoint of vibration isolation. The structure is analysed by the finite element technique where the geometry, the mass, the stiffness and the damping properties of the exhaust pipe are modeled. The validity of the developed model is verified by comparing with the experimental results. An optimization is carried out by the quadratic approximation algorithm. The reaction transferred to an automobile body by the hanger is considered ad the objective function. It is shown that the exhaust system which has the bellows at the optimal position is more effective for the vibrational characteristics than the others. It is also proved that this analytical method is quite useful in the design stage of the exhaust system.

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